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Simultaneous Multiple Rotation Averaging Using Lagrangian Duality

  • Johan Fredriksson
  • Carl Olsson
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7726)

Abstract

Multiple rotation averaging is an important problem in computer vision. The problem is challenging because of the nonlinear constraints required to represent the set of rotations. To our knowledge no one has proposed any globally optimal solution for the case of simultaneous updates of the rotations. In this paper we propose a simple procedure based on Lagrangian duality that can be used to verify global optimality of a local solution, by solving a linear system of equations. We show experimentally on real and synthetic data that unless the noise levels are extremely high this procedure always generates the globally optimal solution.

Keywords

Dual Problem Primal Problem Dual Solution Relative Rotation Primal Solution 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Johan Fredriksson
    • 1
  • Carl Olsson
    • 1
  1. 1.Centre for Mathematical SciencesLund UniversitySweden

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